Virtual Race Car Engineer 2018 Full Crack [full Version]
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Race engineers can see things in the most microscopic of detail. During an NTT INDYCAR SERIES race, they collect millions of bits of data and try to make sense of it to set up a winning race car or develop a winning strategy.
Power and Pagenaud have competed in iRacing since its inception 12 years ago and are elite drivers on the computer-based racing platform. But the addition of their race engineers illustrates how serious these drivers take the INDYCAR iRacing Challenge.
This is a good opportunity because there is not as much data coming in. I think they do a good job with that on NBC trying to explain things. I go into more detail about why a decision is made, and you can see it play out. It happens on a broadcast, and people can see why a decision is made and how it happens.
The NTT INDYCAR SERIES showcases competition at its highest level. Once rival teams saw how well Team Penske was performing in the iRacing Challenge, they decided to get their engineering staff involved.
If you talk to any of the engineers up and down the virtual pit lane, we would love to have open setups on these cars so we can actually twist a few knobs and find speed in them. But we are realistic enough to know if they allowed that, we would be up 24/7. That is the nature of this industry. In some ways, you are handcuffed, but we are working on the communication.
The six-race INDYCAR iRacing Challenge has given race fans a chance to connect with their favorite drivers during an unexpected shutdown to the season. It has also been beneficial from a team standpoint.
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"When you are doing a real [24-hour] race, you have your tyre man asking you for pressure. You have your team manager asking you how you go, you have interactions with lots of people. You have the noise of the cars and you have to be awake to ask the driver to jump in the car. At racing from home you sit basically in a room with computers, no noise, so it is really difficult to keep focused for 24 hours without this adrenaline."
At 3pm French time last Saturday the Virtual 24 Hours of Le Mans got underway, there where many elements that for the competitors differed from the real-life race, which has been postponed to September amid the COVID-19 pandemic.
But even more so than for the drivers swapping a real-life cockpit for their home simulators, the engineers usually camped on the pitwall with ear-plugs in but Porsches screeming by every 4 minutes will feel removed from the action, with none of the same urgency that comes from making race-deciding decisions trackside.
As a technical director for Sebastien Viger called the shots for the team's entry in the Prototype class with pro drivers Kelvin Van der Linde and Dries Vanthoor joined by sim racers Arne Schoonvliet and Fabrice Cornelis. Together with race- and data engineer the virtual race has been prepared and analysed as being live at a race track. "It was really important to avoid mistakes because apart from some avid sim racers, nobody really knows how tired or how physically engaging this 24 hours will be," says Viger. "You have to stay concentrated with no noise, without a direct view of what the pitlane is going to be for example, so the fresher minds in the last two hours will be quite important strategy-wise and also to avoid mistakes.
"In the preparation race we saw at the start, the first lap was a disaster, everybody crashing into each other, so actually that could be quite decisive in the last two hours. For sure the level of the driver will be important, but the winner was the team which avoided mistakes, as in real racing."
Before joining the two-time Spa 24 hour-winning squad in 2017, Viger spent the majority of his career working in GP2/Formula 2 for the Spanish-based Racing Engineering squad, running Swiss driver Fabio Leimer to the 2013 title. He spent the latter two years as technical director, and became very familiar with the team's in-house simulator that ran the same r-Factor platform as been used at the race in Le Mans.
"Obviously previously simulation with RFactor was used as a tool and not used as a race like we see now, but it is just getting bigger and bigger, it evolved quite a lot and we had to adapt quickly. The main thing that we realised early on is maybe you have a bit less of engineering to do compared to some real races, but you also have to keep much more focused."
Nevertheless, with the 30-strong field of prototypes each theoretically capable of the same lap-times - all will using the same Oreca 07 LMP2 model - a good engineering support system had a profound impact in the laptime and as important in the driveability of the car equally for all team members. A well ballanced car will support the driver to concentrate better and so avoid mistakes. And the assumption that the race would be determined very much by strategy next to the car set-up - due to the limitations of the virtual model - have gradually been altered as its preparations intensified and proven in the race.
"The teams started by jumping into the sim racer world really relying on the sim racers feedback, how to deal with the game, what are the tricks for the driving," " then we realised that, 'okay, the car has a bit of oversteer or understeer, let's try this trick from real-life and actually it worked not exactly the same but by its direction.
"It's kind of transformed a bit in the real-world interaction with the drivers, trying set-ups, trying double stints, trying to save some fuel, when to coast and not. All in all, you need to understand how the virtual car is doing but have some real-life parameters you can still improve and do like real. It's funny how it evolved in the last few weeks from pure expectation of only strategy to actually including some [set-up] techniques in the mix."
By the same token, teams have access to even more data than in real-life due to restrictions on where they can put sensors. In the sim you can see litterly everything, which in retrospec shows as well area`s you can think of again on the real car.
"You get data like tyre temperature which is quite difficult to get in real-life because of the regulations. You don't work with the same sensors, especially as some real ones are not present, so I would say you miss some sensors but you have more information from other parts so you can still quite rely on the data you get. You have to work a little differently, but you can still get quite a lot of information. It's quite interesting actually and extents your view of a race car."
The endurance racing pedigree of lead drivers Vanthoor, a winner of the GTE-Am class at Le Mans in 2017 and the 2017 Nrburgring 24h winner van der Linde, are amongest the best of the real GT drivers in the world. Together with sim aces Cornelis and Schoonvliet, they formed a proud Belgian team. "We're used to having a clear demarcation between pro and am, you know when your pro is in you'll be one second quicker than the am, now you have a mix, you have some sim racers who are actually slower than some pro drivers, but you have of course pro drivers that are slower compared to most sim racers.
"Also you have unknown names: normally as a race engineer or team manager they know all the drivers and know what kind of weakness or strength they can have, but if you have an unknown sim racer or an unexperienced pro-race in sim racing, you don't really know them. It's quite difficult to tell your driver if the one that's in front is quicker or to expect some erratic driving, so it will be quite tough from this area.
"It's quite a big inspiration to be able to fight on an equal level with guys like Toyota and Porsche because it can put all on the map of endurance racing as we cannot do at the moment with the real racing."
"The model from the beginning was clear, this is racing. You can call it real racing or virtual racing, but at the end of the day the definition of racing is you have several actors trying to be first and this is what we want to do. Hopefully in the future we'll be there with the real car, but at the end it's a 24-hour Le Mans win that everybody was and is going for."
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Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.
Abstract: In circuit motorsport, race strategy helps to finish the race in the best possible position by optimally determining the pit stops. Depending on the racing series, pit stops are needed to replace worn-out tires, refuel the car, change drivers, or repair the car. Assuming a race without opponents and considering only tire degradation, the optimal race strategy can be determined by solving a quadratic optimization problem, as shown in the paper. In high-class motorsport, however, this simplified approach is not sufficient. There, comprehensive race simulations are used to evaluate the outcome of different strategic options. The published race simulations require the user to specify the expected strategies of all race participants manually. In such simulations, it is therefore desirable to automate the strategy decisions, for better handling and greater realism. It is against this background that we present a virtual strategy engineer (VSE) based on two artificial neural networks. Since our research is focused on the Formula 1 racing series, the VSE decides whether a driver should make a pit stop and which tire compound to fit. Its training is based on timing data of the six seasons from 2014 to 2019. The results show that the VSE makes reasonable decisions and reacts to the particular race situation. The integration of the VSE into a race simulation is presented, and the effects are analyzed in an example race. Keywords: race; simulation; strategy; motorsport; machine learning; neural network; decision making
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